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Clark Quinn’s Learnings about Learning

The ITA Jay Cross Memorial Award for 2018: Mark Britz

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In honor of the colleague, mentor, and friend that brought us together, every year the Internet Time Alliance presents the Jay Cross Memorial Award. The award is for an individual who represents the spirit of continuing informal learning for the workplace. This year, Mark Britz is the deserving recipient.

Jay was a fierce champion of social and informal learning. He saw that most of how we learn to do what we do comes from interacting with others.  As a response to his untimely passing, the remaining members of the ITA decided to honor his memory with an award.  Jane Hart, Harold Jarche, Charles Jennings, & myself each year collectively decide an individual who we think best reflects Jay’s vision. And we announce the recipient on the 5th of July, Jay’s birthday.

Mark has resonated and amplified the message of ongoing learning since we first crossed paths. He has interacted with the ITA members regularly via tweets, blogs, and in person when possible.  And we’ve appreciated his engagement with the ideas and his contributions to our thinking.

I got to know Mark’s thinking a bit better when he wrote a case study based upon his work at Systems Made Simple for the Revolution book (Jay wrote the foreword).  And he’s continued to blog about workplace learning at The Simple Shift with short but insightful posts. Currently part of the team running events for the eLearning Guild, Mark manages to consistently touts views that illuminate thinking about the new workplace.

The situation he cites in that case study is exemplary of this type of thinking. Charged with starting a corporate ‘university’ in an organization that was composed of many experts, he knew that ‘courses’ weren’t going to be a viable approach. Instead, he championed and built a social network that pulled these experts together to share voices. The core L&D role was one of facilitating communication and collaboration, rather than presenting information.

For his continuing work promoting communication, collaboration, and continual learning, we recognize Mark’s efforts with the 2018 Internet Time Alliance Jay Cross Memorial Award.

 

 

Microlearning Malarkey

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Someone pointed me to a microlearning post, wondering if I agreed with their somewhat skeptical take on the article. And I did agree with the skepticism.  Further, it referenced another site with worse implications. And I think it’s instructive to take these apart.  They are emblematic of the type of thing we see too often, and it’s worth digging in. We need to stop this sort of malarkey. (And I don’t mean microlearning as a whole, that’s another issue; it’s articles like this one that I’m complaining about.)

The article starts out defining microlearning as small bite-sized chunks. Specifically: “learning that has been designed from the bottom up to be consumed in shorter modules.” Well, yes, that’s one of the definitions.  To be clear, that’s the ‘spaced learning’ definition of microlearning. Why not just call it ‘spaced learning’?  

It goes on to say “each chunk lasts no more than five-then minutes.” (I think they mean 10). Why? Because attention. Um, er, no.  I like JD Dillon‘s explanation:  it needs to be as long as it needs to be, and no longer.

That attention explanation?  It went right to the ‘span of a goldfish’. Sorry, that’s debunked (for instance, here ;).  That data wasn’t from Microsoft, it came from a secondary service who got it from a study on web pages. Which could be due to faster pages, greater experience, other explanations. But not a change in our attention (evolution doesn’t happen that fast and attention is too complex for such a simple assessment).  In short, the original study has been misinterpreted. So, no, this isn’t a good basis for anything having to do with learning. (And I challenge you to find a study determining the actual attention span of a goldfish.)

But wait, there’s more!  There’s an example using the ‘youtube’ explanation of microlearning. OK, but that’s the ‘performance support’ definition of microlearning, not the ‘spaced learning’ one. They’re two different things!  Again, we should be clear about which one we’re talking about, and then be clear about the constraints that make it valid. Here? Not happening.  

The article goes on to cite a bunch of facts from the Journal of Applied Psychology. That’s a legitimate source. But they’re not pulling all the stats from that, they’re citing a secondary site (see above) and it’s full of, er, malarkey.  Let’s see…

That secondary site is pulling together statistics in ways that are  thoroughly dubious. It starts citing the journal for one piece of data, that’s a reasonable effect (17% improvement for chunking). But then it goes awry.  For one, it claims playing to learner preferences is a good idea, but the evidence is that learners don’t have good insight into their own learning. There’s a claim of 50% engagement improvement, but that’s a mismanipulation of the data where 50% of people would like smaller courses. That doesn’t mean you’ll get 50% improvement. They also make a different claim about appropriate length than the one above – 3-7 minutes – but their argument is unsound too. It sounds quantitative, but it’s misleading. They throw in the millennial myth, too, just for good measure.

Back to the original article, it cites a figure not on the secondary site, but listed in the same bullet list: “One minute of video content was found to be equal to about 1.8 million written words”.  WHAT?  That’s just ridiculous.  1.8 MILLION?!?!?  Found by who?  Of course, there’s no reference. And the mistakes go on. The other two bullet points aren’t from that secondary site either, and also don’t have cites.  The reference, however could mislead you to believe that the rest of the statistics were also from the journal!

Overall, I’m grateful to the correspondent who pointed me to the article. It’s hype like both of these that mislead our field, undermine our credibility, and waste our resources. And it makes it hard for those trying to sell legitimate services within the boundaries of science.  It’s important to call this sort of manipulation out.  Let’s stop the malarkey, and get smart about what we’re doing and why.  

A good publisher

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I shot this short little video because, well, I have to say that my experience with ATD has been excellent. They’ve done what I’ve needed: listening when they should, arguing with me when they should, responding to my questions, and executing on their responsibilities professionally. They’ve gone above and beyond, and I’m pleased to have them as my publisher on my most recent tome.

If you’re going to complain about the bad things (or, at least, make fun of them :), I reckon you should highlight the good ones too.  They showed their capabilities while serving as co-publisher on my last book, and now they’ve demonstrated the whole deal. Thanks, team!

A solid education platform

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In the past couple of days, I’ve come across two different initiatives to improve education. And certainly our education system can stand improvement. However, each one had the same major flaw, and leaves open an opportunity for improvement not to occur. Over a number of engagements I’ve developed the basis of what I think is a necessary foundation for a viable education platform. It’s time to toss it out and see what you all think.

So, one initiative had a proposal of 10 different areas they wanted people to contribute in. This included AI, and personalization, and ‘out of class’ credit, and more. Which is all good, make no mistake! However, nowhere was there the option of ‘a deeper pedagogy’. And that’s a problem. It’s all too easy to chase after the latest shiny object. It makes us feel like we’re both doing something constructive and keeping up with developments. (Not to mention how much fun it is to play with the latest things.) However, gilding bad design is still bad design! We need to make sure the foundation is strong before we go further.

The other initiative has three ways to contribute: lifelong learning, a marketplace, and emerging technology. And, again, the big gap is talking about the pedagogy to begin with.  With a marketplace, you might get some Darwinian selection process, but why not put it out there from the get-go? Otherwise, it’s just cool tinkering around a broken core.

Three partsSo here’s where I pitch my 3 part story. Note that curriculum is broken too (I’m channeling Roger Schank: ‘Only two things wrong with education, what we teach and how we teach it’), and yet I’m not addressing that. Well, only a second layer of curriculum (see below ;). I think the choice of the first level curriculum is a big issue, but that changes depending on level, goals, etc. Here I’m talking about a platform for delivering the necessary elements of a supportable approach:

  1. The first element is a killer learning experience. What do I mean here? I mean an application-based learning approach. Even for so-called theory classes (e.g. typical higher ed), you  do something with this. And the experience is based upon minimal content, appropriate challenge, intrinsic motivation, and more. My claim: this is doable, even when you want to auto-mark as much as possible. Of course, there are still people in the loop.
  2. Which leads to the second element, we as the provider are a partner in your success. It’s not ‘sink or swim’, but instead we’re tracking your progress, intervening when it looks like you’re struggling, and accessible at your time and place. We’re also providing the necessary resources to succeed. And we’re not interested in a curve, we’re competency-based and want everyone to get where they can be.  We’re also making sure you’re getting what you need.
  3. And that’s the third element, we  develop you. That is, we’re not just developing your knowledge of the field, we’re also developing key success skills. That means we’re giving you chances to practice those skills as well,  and tracking them and developing them as well. This includes things like communication, collaboration, design research, and more. So-called 21C skills.

I suggest that with such an approach, and the right curriculum, you’re providing a full suite of what education  should  be about. And, I suggest, we can do this now, affordably. Technology is part of the picture, learning science is part of the picture, and the commitment to do the right thing is part of the picture. Also, I think this is viable at all levels. K12, higher ed, and workplace.

And, I’ll suggest, anything less really isn’t defensible. We have the know-how, we have the tools, all we need is the will. Yet, despite some notable steps in the right direction, we’re really not there. It’s time to put a stake in the ground. Who’s up for it?

Quip: Learning & Development

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I’ve used this quip quite a bit, as it’s essentially the rationale for the Revolution book.  And I want to make clear what I’m saying, and then qualify it.  It’s about the state of Learning & Development, and sums up one perspective fairly succinctly:

L&D isn’t  doing near what it could and should be, and what it is doing it’s doing badly. Other than that, it’s fine.

It’s meant to be a little flip and ‘in your face’, but it’s because I think there’s such potential for L&D!  This is my way of characterizing the situation that might spark some reflection, and even action.

L&D is, largely, about courses.  And unfortunately, too often they’re about content-dump, and an experience that will rank highly on a smile sheet. Which is historically understandable, but scientifically bereft. Compliance aside (and here’s to a competency shift, away from ‘1 hour / year’ or whatever other time-based basis we might find), our courses should be focused on applying knowledge to meaningful tasks, and meaningful feedback. Sufficient, varied, spaced, and deliberate practice!  Of course this isn’t everyone’s L&D, but it certainly appears to be all too present.

The second thing is that L&D could be so much broader!  If we’re really worry about organizational performance and continuing improvement (why I suggest L&D should shift to P&D, performance and development), we should do more. Performance support, for instance, should be under the purview of L&D. Otherwise it gets left to chance or those who don’t have the necessary background.

And, then there’s coaching. Recognize that learning takes time, and that we need to continue development beyond the classroom. Thus, coaching’s critical to continued improvement. Again, L&D has a role to play here: developing coaching skills, providing guidance, and tracking.

Then we go beyond formal learning: optimizing the ongoing learning in individuals, teams, and communities. This is organizational learning! There’re processes for individual improvement like PKM, team processes like brainstorming, and community interactions. Leaving these to chance is a mistake, as we can’t assume these skills.

And the outcomes of helping the organization get better beyond the course are big. Not just individual learning, but the organization is learning faster. And that’s a necessity for success, going forward. In short, there’s a lot L&D could be doing that would help the organization that it’s missing now.

Now, complaining as my statement does isn’t necessarily useful, unless it’s constructive, and the point is that we have very comprehensive and specific things we know about doing better.  By this quip I don’t mean to criticize; I want to inspire action and improvement. So here’s to revolutionizing L&D. I hope you’ll join us!

Services

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From time to time, it’s worth a reminder that Quinnovation (the firm behind the blog) is available to help you.  Here are the services you can look to from me, in case you want to accelerate your success.

And a wee bit of self-promotion: if expertise comes from years of practice, how about 3+ decades of investigating the breadth and depth of learning & performance, and exploration of technology support?  Why not get assistance from where the thinking originates, not the several-steps away diluted version?

Consulting:

Learning Design: are your design processes yielding the outcomes they should and need to? I have worked with many organizations to generate or tighten learning design processes to reflect learning science (not myths). I recognize that most organizations can’t completely revamp their approaches, so I look to the small changes with the biggest impact. A white paper talks about this.

Performance Ecosystem Strategy: are you leading your organization forward in learning (read: innovation) or are you still taking orders for courses?  Based on the book, I’ve helped a number of organizations understand the full spectrum of possibilities, evaluate their situation, and prioritize short-, medium-, and long-term steps.  Another white paper talks about this.

Games & Mobile: I’ve helped a number of organizations get their minds, strategies, and design processes around mobile and/or games, based upon  those  books.

Workshops

Want to get your team up to speed on learning science, strategy, games, mobile, or more?  I have workshops on each that are interactive, engaging, and effective. Preferably, they’re coupled with followup to extend the learning (applying the learning science), and that can be done in a variety of ways.

Presentations

A number of organizations around the world have booked me to speak to their audiences. They have been about the subjects of my books, or the future of learning technology in general. And have indicated they were quite satisfied with the result ;). If you want a credible, engaging presenter around intelligence augmentation, I’m a candidate.

Writing

In addition to books, I write white papers, blog posts, and articles for others. I could do the same for you.

Coaching

If you’re a learning leader that would like assistance over time addressing your organization’s needs, it would certainly be worth a conversation. I haven’t done this formally, but it seems like a natural extension.

And, of course, there are combinations of these services as well. You can find out more at the official Quinnovation site. Next week we return you to your regularly scheduled blog at this same channel.

Nuances Matter

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I’ve argued before that the differences between well-designed and well-produced learning, and just well-produced learning, are subtle. And, in general, nuances matter. So, in my recent book, the section on misconceptions spent a lot of time unpacking some terms. The goal there was ensuring that the nuances were understood. And a recent event triggered even more reflection on this.

Learnnovators, a company I’ve done a couple of things with (the Deeper eLearning series, and the Workplace of the Future project), interviewed me once quite a while ago. I was impressed then with the depth of their background research and thoughtful questions. And they recently asked to interview me on the book. Of course, I agreed. And again they impressed me with the depths of their questions, and I realized in this case there was something specific going on.

In their questions, they were unpacking what common concerns would be about some of the topics.  The questions dug in to ways in which people might think that the recommendations are contrary to personal experience, and more.  There were very specifically looking for ways in which folks might think to reject the findings.  And that’s important. I believe I had addressed most of them in the book, but it was worth revisiting them.

And that’s the thing that I think is important about this for our practice. We can’t just do the surface treatment. If we just say: “ok we need some content, and then let’s write a knowledge test on it”, we’ve let down our stakeholders.  If we don’t know the cognitive properties of the media we use, don’t sweat the details about feedback on assessment, don’t align the practice to the needed performance, etc., we’re not doing our job!

And I don’t mean you have to get a Ph.D. in learning science, but you really do need to know what you’re doing. Or, at least, have good checklists and quick reference guides to ensure you’re on track. Ideally, you review your processes and tools for alignment to what’s known. And the tools themselves could have support. (Ok, to a limit, I’ve seen this done to the extent of handcuffs on design.)

Nuances matter,  if you care about the outcomes (and if you don’t, why bother? ;).  I’ve been working on both a checklist and on very specific changes that apply to various places in design processes that represent the major ways folks go wrong. These problems are relatively small, and easy to fix, and are designed to yield big improvements. But unless you know what they are, you’re unlikely to have the impact you intend.

Context is key

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Workflow learning is one of the new buzzphrases. The notion is that you deliver learning to the point of need, instead of taking people away from the workflow. And I’m a fan. But it’s not as easy as it sounds!  Context is a critical issue in making this work, and that’s non-trivial.

When we create learning experiences, typically we do (or should) create an artificial context for learners to practice in. And this makes sense when the performance has high consequences.  However, if people are in the workflow, there is a context already. Could we leverage that context for learning instead of creating one?  When would this make sense?

I’d suggest that there are two times workflow learning makes sense. For one, if the performers aren’t novices, this becomes an opportunity to provide learning at the point of need to elaborate and extend learning. Say, refining knowledge on sales, marketing, or product when touching one of them.  For another, it would make sense if the consequences aren’t high and the ease of repair is easy. So, sending on a workpiece that will get checked anyways.

Of course, we  could just do performance support, and not worry about the learning, but we can do that  and support learning as well. So, having an additional bit of learning content at the right time, whether alone or in conjunction with performance support, is a ‘good thing’.  The difficulties come when we get down to specifics.

Specifically,  how do we match the right content with the task? There are several ways. For one, it can just be pull. Here the individual asks for some additional help and/or learning. This isn’t completely trivial either, because you have to have a search mechanism that makes it easy for the performer to get the right stuff. This means federated search, vocabulary control, and more. Nothing you shouldn’t already be worrying about for pull learning anyways, but for the record.

Second, you could do push. Here it gets more dicey.  One way is to have content tied to specific instances. This can be hand done as some tools have made possible. That is, you instrument content with help where you find, or think, it could be needed. The other way is to be smart  about  the context.

And this is where it gets complicated. For such workflow learning to work, you really want to leverage the context, so you need to be able to  identify  the context.  How do you know what they’re doing? Then you need to map that context to content. You could use some signal (c.f. xAPI) that tells you when someone touches something. Then you could write rules that map that touch to the associated content. It might even by description, not hardwired, so the system’s flexible. For instance, it might change the content depending on how many times and how recently this person has done this task.  This is all just good learning engineering, but the details matter.

Making workflow learning work is a move towards a more powerful performance ecosystem and workforce, but it requires some backend effort.  Not surprising, but worth being clear on.

Real (e)Learning Heroes

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Super logoWhile there are people who claim to be leaders in elearning (and some are), there is another whole group who flies under the radar. These are the people who labor quietly in the background on initiatives that will benefit all of us. I’m thinking in particular of those who work to advance our standards. And they’re really heroes for what they’ve done and are doing.

The initial learning technology standards came out from the AICC.  They wanted a way to share important learning around flight, an area with a big safety burden.  Thus, they were able to come together despite competition.

Several other initiatives include IEEE (which is pretty much  the US based effort on electric and electronic technology standards to the international stage), and the IMS efforts from academia.  They were both working on content/management interoperability, when the US government put it’s foot down. The Department of Defense’s ADL initiative decided upon  a  version, to move things forward, and thus was born SCORM.

Standards are good. When standards are well-written, they support a basis upon which innovation can flourish.  Despite early hiccups, and still some issues, the ability for content written to the standards to run on any compliant platform, and vice versa, has enabled advancements. Well, except for those who were leveraging proprietary standards.  As a better example, look how the WWW standard on top of the internet standards has enabled things like, well, this blog!

Ok, so it’s not all roses.  There are representatives who, despite good intentions, also have vested interests in things going in particular directions. Their motivations might be their employers, research, or other agendas.  But the process, the mechanisms that allow for decision making, usually end up working. And if not, there’s always the ADL to wield the ‘800 lb gorilla’ argument.

Other initiatives include xAPI, sponsored by ADL to address gaps in SCORM. This standard enables tracking and analytics  beyond the course. It’s no panacea, but it’s a systematic way to accomplish a very useful goal. Ongoing is the ICICLE work on establishing principles for ‘learning engineering’, and IBSTPI  for training, performance, and instruction.  Similarly, societies such as ATD and LPI try to create standards for necessary skills (their lists are appendices in the Revolution book).

And it’s hard work!  Trying to collect, synthesize, analyze, and fill in gaps to create a viable approach requires much effort both intellectual  and social!  These people labor away for long hours, on top of their other commitments in many cases.  And in many cases their organizations support their involvement, for good as well as selfish reasons such as being first to be able to leverage the outputs.

These people are working to our benefit. It’s worth being aware, recognizing, and appreciating the work they do.  I certainly think of them as heroes, and I hope you will do so as well.

New and improved evaluation

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A few years ago, I had a ‘debate’ with Will Thalheimer about the Kirkpatrick model (you can read it here).  In short, he didn’t like it, and I did, for different reasons.  However, the situation has changed, and it’s worth revisiting the issue of evaluation.

where kirkpatrick fitsIn the debate, I was lauding how Kirkpatrick  starts with the biz problem, and works backwards. Will attacked that the model didn’t really evaluate learning. I replied that it’s role wasn’t evaluating the effectiveness of the learning design on the learning outcome, it was assessing the impact of the learning outcome on the organizational outcome.

Fortunately, this discussion is now resolved. Will, to his credit, has released his own model (while unearthing the origins of Kirkpatrick’s work in Katzell’s).  His model is more robust, with 8 levels.  This isn’t overwhelming, as you can ignore some. Fortunately, there’re indicators as to what’s useful and what’s not!

It’s not perfect. Kirkpatrick (or Katzell? :) can relatively easily be used for other interventions (incentives, job aids, … tho’ you might not tell it from the promotional material). It’s not so obvious how to do so with his new model.  However, I reckon it’s  more robust for evaluating learning interventions. (Caveat: I may be biased, as I provided feedback.) And  should he have numbered them in reverse, which Kirkpatrick admitted might’ve been a better idea?

Evaluation is critical.  We do some, but not enough. (Smile sheets, level 1, where we ask learners what they think of the experience, has essentially zero correlation with outcomes.) We need to do a better job of evaluating our impacts (not just our efficiency). This is a more targeted model.  I draw it to your attention.